Web Resources Research Articles

Towards routine proteome profiling of FFPE tissue: insights from a 1,220-case pan-cancer study

AbstractProteome profiling of formalin-fixed paraffin-embedded (FFPE) specimens has gained traction for the analysis of cancer tissue for the discovery of molecular biomarkers. However, reports so far focused on single cancer entities, comprised relatively few cases and did not assess the long-term performance of experimental workflows. In this study, we analyze 1220 tumors from six cancer entities processed over the course of three years. Key findings include the need for a new normalization method ensuring equal and reproducible sample loading for LC-MS/MS analysis across cohorts, showing that tumors can, on average, be profiled to a depth of >4000 proteins and discovering that current software fails to process such large ion mobility-based online fractionated datasets. We report the first comprehensive pan-cancer proteome expression resource for FFPE material comprising 11,000 proteins which is of immediate utility to the scientific community, and can be explored via a web resource. It enables a range of analyses including quantitative comparisons of proteins between patients and cohorts, the discovery of protein fingerprints representing the tissue of origin or proteins enriched in certain cancer entities.

XSShield: A Novel Dataset and Lightweight Hybrid Deep Learning Model for XSS Attack Detection

With the proliferation of web applications, cross-site scripting (XSS) attacks have increased significantly and now pose a significant threat to users' information security and privacy. To enhance the efficiency of XSS attack detection, the adoption of machine learning (ML) and deep learning (DL) techniques offers promising solutions, but their effectiveness is limited by the lack of comprehensive and diverse datasets. Moreover, existing approaches often prioritize detection accuracy over real-time processing capabilities, which are essential for effective defense. To address these challenges, in this paper, we propose a novel framework that automatically collects web resources, efficiently extracts informative features, and constructs an up-to-date XSS attack dataset, which is then used to train a machine learning-based XSS detection model. Using this framework, we created and published a well-structured dataset over 100,000 samples for the research community. Furthermore, we present a hybrid detection model that leverages the strengths of both Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. Extensive evaluations of our dataset demonstrate that the proposed model outperforms other baseline ML models across various metrics, including processing rate. Notably, our model achieves an accuracy of 99.27% while maintaining a low false positive rate of 0.06% and high processing rate of exceeding 1000 samples per second. These results highlight its high accuracy and robustness in detecting XSS, and suitability for real-time applications. Our work presents a comprehensive solution for enhancing web application security by providing a diverse dataset and a high-accuracy detection model with low latency.

BGC Atlas: a web resource for exploring the global chemical diversity encoded in bacterial genomes.

Secondary metabolites are compounds not essential for an organism's development, but provide significant ecological and physiological benefits. These compounds have applications in medicine, biotechnology and agriculture. Their production is encoded in biosynthetic gene clusters (BGCs), groups of genes collectively directing their biosynthesis. The advent of metagenomics has allowed researchers to study BGCs directly from environmental samples, identifying numerous previously unknown BGCs encoding unprecedented chemistry. Here, we present the BGC Atlas (https://bgc-atlas.cs.uni-tuebingen.de), a web resource that facilitates the exploration and analysis of BGC diversity in metagenomes. The BGC Atlas identifies and clusters BGCs from publicly available datasets, offering a centralized database and a web interface for metadata-aware exploration of BGCs and gene cluster families (GCFs). We analyzed over 35000 datasets from MGnify, identifying nearly 1.8 million BGCs, which were clustered into GCFs. The analysis showed that ribosomally synthesized and post-translationally modified peptidesare the most abundant compound class, with most GCFs exhibiting high environmental specificity. We believe that our tool will enable researchers to easily explore and analyze the BGC diversity in environmental samples, significantly enhancing our understanding of bacterial secondary metabolites,and promote the identification of ecological and evolutionary factors shaping the biosynthetic potential of microbial communities.

Studying technical sciences without borders: We use the navigator for open educational resources. Part 1. The Russian experience

Introduction. The introduction of information and communication technologies into learning processes expands the possibilities of using information resources and becomes one of the priorities of the transforming higher education system. These changes are reflected in the trends in the development and application of open educational resources. However, the scale and fragmentation of data on the Internet, as well as the lack of open educational resources standards, makes the information retrieval process a difficult task and requires professional skills.Purpose setting. To determine the relevance and prospects for the development of sectoral open educational resources, it is necessary to analyze their role in the modern educational system. It is important to identify the possibilities of using open access research in technical sciences as one of the tools to eliminate social inequality in higher education. To identify and present arguments for the purpose of justifying the need to develop an industry-specific «Navigator on OER of Technical Sciences» (hereinafter referred to as the «Navigator»).Methodology and methods of the study. The research methodology covers the study and analysis of scientific papers devoted to the development of tools and initiatives in the field of open educational resources in technical sciences both in Russia and abroad. This study is also based on the method of oral questioning of students, postgraduates and teachers of technical disciplines at universities in Novosibirsk. Results. An array of scientific literature and web resources has been studied, providing free access to scientific and educational information in the field of research under consideration. Taking into account empirical data, the necessity of developing a «Navigator» on open educational resources in the system of higher technical education is justified (http://lib-os.ru/issledovatelyam/resursy/obrazovatelnye- resursy/navigator-oor-techn-nauk/).Conclusion. The study of technical sciences using open educational resources contributes to the effective improvement of professional level and allows you to be aware of current solutions to innovative activities in the field of knowledge under consideration.

Trophic Structure of Fish Community in Artificial Reef Ecosystem Based on Body Mass Using Stable Isotope

Artificial reefs are widely recognized for their role in improving the ecological environment and creating protected habitats for marine organisms, ultimately enhancing biodiversity within the food web and fisheries resources. This study utilizes stable isotopes to analyze fish samples ranging from 3.4 to 1067 g in body mass, collected within the artificial reef area of Haizhou Bay. The objective is to determine if the δ15N-based fish body mass acts as a driving factor in shaping the food web structure. The results showed a certain level of overlap among all trophic guilds, suggesting that most trophic guilds within this region share similar living environments and feeding habits. The multiple linear regression showed a slight increasing trend between δ15N values and body mass. Furthermore, the predator–prey mass ratio (PPMR) was calculated to be 430:1 based on the δ15N–body mass relationship. This implies that larger reef fish within this artificial reef ecosystem tend to have higher δ15N values compared to smaller fish, indicating a shorter food chain in this ecosystem. In summary, this analysis provides valuable insights into the fish community structure within artificial reef ecosystems. Therefore, it is recommended that future studies focus on further characterizing the fish community structure using body mass information.

A Comprehensive Overview of Internet of NanoThings and its Applications

INTRODUCTION: Internet of NanoThings (IoNT) is regarded as the next generation of the Internet of Things due to its bright future and wide range of applications . According to the global "Internet of Nanothings (IoNT) Market" research, there has been good growth in recent years, and this trend is expected to continue until 2030. IoNT is basically the Internet of Things on a nanoscale. IoNT essentially describes how nanoscale devices are connected to one another within current networks. A high-speed network can be used to connect different nanodevices through the IoNT. This study provides a comprehensive overview of the architecture, benefits and applications of IoNT. OBJECTIVES: The objective is to provide insights into IoNT framework and it applications in fields like healthcare, food industry, agriculture , environment monitoring etc, METHODS: This study explored the IoNT architecture and its applications. The exploration involves reviewing the articles, journals and other web resources. RESULTS: Highlights the aspects of IoNT and emphasizing the importance of its applications in various fields. The need to combine this research and emphasize the IoNT related applications stems from the dearth of research in the field. CONCLUSION: The world is becoming increasingly developed as a result of ongoing technological advancements. Future developments, which are expected to peak in the next one to two decades, will be led by IoT and nanotechnology. IoNT offers potential and means to enhance numerous facets of individuals' lives. Its primary characteristics are monitoring and diagnostic services, which support and improve decision-making and outcomes across a range of application domains.

Bioinformatic Resources for Exploring Human-virus Protein-protein Interactions Based on Binding Modes.

Historically, there have been many outbreaks of viral diseases that have continued to claim millions of lives. Research on human-virus protein-protein interactions (PPIs) is vital to understanding the principles of human-virus relationships, providing an essential foundation for developing virus control strategies to combat diseases. The rapidly accumulating data on human-virus PPIs offer unprecedented opportunities for bioinformatics research around human-virus PPIs. However, available detailed analyses and summaries to help use these resources systematically and efficiently are lacking. Here, we comprehensively review the bioinformatic tools used in human-virus PPIs research, discuss and compare the function, performance, and limitations of these web resources. This study aims to provide researchers with a bioinformatic toolbox that will hopefully better facilitate the exploration of human-virus PPIs based on binding modes.

Formation of a Unified Educational Space of the Union State from the Perspective of the Policy of Patriotic Education

Introduction. Awareness of the commonality of geopolitical and civilizational challenges of the Russian Federation and the Republic of Belarus pushes for deepening integration cooperation in different directions. Close attention is paid to the problem of security, interpreted in an expanded way. Its provision correlates with the strengthening of the humanitarian dimension of the Union State, including the formation of a unified educational space. In modern conditions, its correlation with the consolidation of the policy of patriotic education in the integration field is being actualized. The purpose of the article is to identify the specifics of their coupling, taking into account the dynamics of union construction. Materials and Methods. The research is based on the methods of binary comparison, traditional and discourse analysis of official texts. An additional method is a formalized correspondence expert survey. The key materials are normative legal acts of the Russian Federation and the Republic of Belarus, interstate, intergovernmental and integration agreements, information content of the web resources of the Union State. The theoretical and methodological foundations of the research are a new political institutionalism, a multidimensional model of social action, and the paradigm of “political unification”. Results. The article describes the normative foundations of state policy in the field of education and integration guidelines in the cultural and humanitarian plane within the framework of the movement towards the Union educational space. The demanded categories of the axiological plan are revealed, referring to the relationship between education and upbringing. The key lines of discursive practices at the sites of the union institutions are shown. The understanding of the need to adapt education systems to the requirements of the time and the linking of patriotic education with the protection and preservation of common historical memory are emphasized. Discussion and Conclusion. The results of the study and expert assessments suggest the articulation of not only positive changes, but also urgent vectors for improving national approaches and integration solutions. They correspond to the elimination of conflicts, the development and adoption of new documents at the level of the Union State, the implementation of value categories and new areas of unified policy. The results obtained may be of interest to public authorities and union institutions, participants in patriotic education in the territory of the Union State.

ENHANCING THE RESILIENCE OF IOT NETWORKS: STRATEGIES AND MEASURES FOR MITIGATING DDOS ATTACKS

The Internet of Things (IoTs) are emerging and become a vital need in our daily routine. The privacy protection and insecurity of these IoT-based devices face many challenges. Distributed denial of service (DDoS) attacks in IoT networks become a significant growing challenge that is addressed in this research. The resilience and strategy for IoT devices due to distributed denial of service (DDoS) attacks assess current security measures by proposing modern procedures to upgrade the strength of IoT frameworks. This article proposes a mechanism that mitigiates the effects of DDoS attacks in IoTs, that cause significant destruction to existing systems. Utilizing secondary data from Kaggle, the machine is trained and tested. Our proposed approach incorporates descriptive statistics, correlations, t-tests, chi-square tests, and regression analyses to supply a systematic understanding of IoT security by critically analyzing the existing variants of numerous DDoS attacks, Security issues in IoTs, and creation of them in Botnets or zombies. Our findings show that the proposed security techniques are viable and detection rates correlate with security viability. The proposed model asses various network threat and cybersecurity arrangements for mitigating DDoS attacks in IoT’s and outperforms the previously implemented Web Application Firewall (WAF), Bot Mitigation, Resource Prioritisation, and Content Delivery Networks (CDNs)based DDoS mitigation techniques by 80.5%, 88%, 86% in terms of effectiveness, T-test, chi test, and correlation.

Kako se izogniti potvorjeni znanosti?

Purpose: The falsification of research data and ideas is not a new phenomenon in scientific communication, nor is it specifically related to open science, rather to the issue of web resources in general. Access to scientific publications has become even faster, cheaper and more accessible for the user. Unfortunately, misleading publishers, and sometimes the researchers themselves, are becoming increasingly inventive. Cooperation with such entities affects (non)evaluation of publications and creates a broader social problem. Not only are publications questionable but the use or misuse of such untrusted sources is also objectionable. Such practices adversely affect the development of society as a whole. Non-experts portray themselves as experts and refer to unverified, misleading scientific publications to justify their attitudes towards current social issues. In communication, including academic writing, we are witnessing a growing lack of knowledge and inability to think critically and an increasingly aggressive justification of the personal aspect as the only acceptable approach. One consequence is also the growing general mistrust in science and, in extreme cases, even deaths due to incorrect decisions by individuals, based on unverified claims and sources that appear to be scientific. Methodology: We have identified tools, platforms, and procedures that help identify and evaluate these practices, and are helpful to researchers and authors in selecting sources and publications in which to publish their findings. Results: The University of Maribor informs students and employees about this issue at lectures, and we have also prepared some research guides in which we try to raise awareness of the user, encourage them to think critically, and at the same time introduce them to the ways and tools that help them detect misleading practices

A holistic view over ontologies for Streaming Linked Data

Streaming Linked Data represents a domain within the Semantic Web dedicated to incorporating Stream Reasoning capabilities into the Semantic Web stack to address dynamic data challenges. Such applied endeavours typically necessitate a robust data modelling process. To this end, RDF Stream Processing (RSP) engines frequently utilize OWL 2 ontologies to facilitate this requirement. Despite the rich body of research on Knowledge Representation (KR), even concerning time-sensitive data, a notable gap exists in the literature regarding a comprehensive survey on KR techniques tailored for Streaming Linked Data. This paper critically overviews the key ontologies employed in RSP applications, evaluating their data modelling and KR abilities specifically for Streaming Linked Data contexts. We analyze these ontologies through three distinct KR perspectives: the conceptualization of streams as Web resources, the structural organization of data streams, and the event modelling within the streams. An analytical framework is introduced for each perspective to ensure a thorough and equitable comparison and deepen the understanding of the surveyed ontologies.

In silico Profiling and Pharmacokinetic Modelling of Olivetol: Evaluating its Potential as a Therapeutic Agent for Diabetic Wound Healing.

Diabetic wound healing poses a significant challenge due to the intricate disruptions in cellular and molecular processes induced by hyperglycaemia, leading to delayed or impaired tissue repair. Computational techniques offer a promising avenue for unravelling the complexities of diabetic wound healing by elucidating the molecular mechanisms involved. This study utilized in silico molecular docking and dynamics simulations to explore the potential therapeutic effectiveness of olivetol, a phenolic compound, in the context of diabetic wound healing. Furthermore, computational methodologies, encompassing pkCSM, Swiss ADME, OSIRIS® property explorer, PASS online web resource, and MOLINSPIRATION® software, were employed to forecast the pharmacokinetic properties, biological actions, and in vitro analyses, such as MTT and scratch assays, to evaluate the therapeutic effectiveness of olivetol in wound healing. Our findings have revealed olivetol to be a promising candidate for targeting multiple pathways implicated in diabetic wound healing. Its ability to modulate inflammation, oxidative stress, extracellular matrix remodeling, angiogenesis, and cell signaling suggests a multifaceted approach to promoting effective wound repair. Moreover, olivetol has been found to demonstrate strong binding affinity with key MRSA target proteins, indicating its potential as an antimicrobial agent against MRSA infections in diabetic wounds. The in vitro MTT assay demonstrated cell viability with an IC50 value of 40.80 μM, highlighting its cytotoxicity potential. Additionally, the scratch assay confirmed promising wound healing activity, showcasing its effectiveness in promoting cell migration and closure. Olivetol emerges as a promising candidate for targeted interventions in non-healing diabetic wounds, particularly due to its ability to address prolonged inflammation, a common obstacle in diabetic wound healing.

MATHEMATICAL MODEL AND STRUCTURE OF A NEURAL NETWORK FOR DETECTION OF CYBER ATTACKS ON INFORMATION AND COMMUNICATION SYSTEMS

The paper discusses the principles of creating a mathematical model and system architecture by applying the method of artificial intelligence to detect cyberattacks on information and communication systems, where a neural network capable of learning and detecting cyberattacks is used. The proposed approach, based on the application of the developed mathematical model and architecture of artificial neural networks, as a detector of network attacks on information and communication systems, allows to increase the level of detection of network intrusions into computer systems, Web and Internet resources. An algorithm for processing network traffic parameters in real-time systems by structuring a neural network is proposed, which allows to optimize the redundancy of its multi-level structure at the level of inter-element connections.

Web reference decay: Passing the HTTP errors instead of quality information

Web resource links routinely fail, and the content of links might change suddenly and without notice. When referrals to online sites offer proof or supporting data, these web dynamics are harmful. Any hyperlink’s final content is susceptible to two phenomena: the link breaks (link rot) and the content changes from its original state (content drift). The combination of both effects is referred to as reference rot. This paper aims to determine the application of online citations, the number of lost web citations, and the process of recovering missing web citations through the application of the Internet Archive’s Wayback Machine. According to the analysis, the Webology journal published 428 research articles between 2004 and 2020 that had 2,273 online citations. There are 1,260 (55.43%) accessible web citations out of the mentioned ones, whereas 1,013 (44.57%) are missing. There are 1,856 (81.65%) active web citations, up from 1,260 (55.43%) after an effort was made to retrieve 596 lost web citations using the Wayback Machine tool. That meant that the overall increase of the active URLs was 26.22%. The article presents a method for creating specific collections for online archiving in the future, even though web-archiving tools now take snapshots of websites in real time. The paper recommends that future curation standards for real-time web archiving shall include platform dynamics and cultural variations in link-sharing habits.

Environmental Implications of Fly Ash Management and Utilization: A Review of Laws, Policies, and Practices.

In the environmental realm, ‘fly-ash’ refers to the byproduct of burning pulverized coal in thermal power stations. One of India's most resource-intensive and polluting industries, coal-fired power generation, contributes considerably to atmospheric pollution. Public power stations that use coal or lignite to generate energy account for 77% of the nation's total electricity production. This sector is responsible for over 65% of India's total coal use. This study employs a multifaceted approach combining theological, exploratory, analytical, and descriptive methods. It relies on secondary sources from diverse web resources to analyze fly ash's ecological and health impacts, explore utilization methods, and discuss potential legislation to prevent careless disposal. The coal-based power industry has added 32 GW, or over 64% of the new massive capacity, to its operations in the last decade, leading to a rise in coal consumption. There was a greater than 71% increase in annual coal usage, from 367 million tonnes in 2009–10 to almost 629 million tonnes in 2018–19. The increasing usage of coal in India has led to fly ash being one of the country's most significant industrial solid wastes. Fly ash is a residue or byproduct made when coal is burned; it is harmful to both humans and the environment. The problem is particularly acute in India because of the poor calorific value, high ash content, and low grade of the coal used there.

Daily life in the Open Biologist's second job, as a Data Curator.

Data reusability is the driving force of the research data life cycle. However, implementing strategies to generate reusable data from the data creation to the sharing stages is still a significant challenge. Even when datasets supporting a study are publicly shared, the outputs are often incomplete and/or not reusable. The FAIR (Findable, Accessible, Interoperable, Reusable) principles were published as a general guidance to promote data reusability in research, but the practical implementation of FAIR principles in research groups is still falling behind. In biology, the lack of standard practices for a large diversity of data types, data storage and preservation issues, and the lack of familiarity among researchers are some of the main impeding factors to achieve FAIR data. Past literature describes biological curation from the perspective of data resources that aggregate data, often from publications. Our team works alongside data-generating, experimental researchers so our perspective aligns with publication authors rather than aggregators. We detail the processes for organizing datasets for publication, showcasing practical examples from data curation to data sharing. We also recommend strategies, tools and web resources to maximize data reusability, while maintaining research productivity. We propose a simple approach to address research data management challenges for experimentalists, designed to promote FAIR data sharing. This strategy not only simplifies data management, but also enhances data visibility, recognition and impact, ultimately benefiting the entire scientific community.

Extendable Essay as a Web Resource for Supporting Lecture Courses

Extendable Essay as a Web Resource for Supporting Lecture Courses

GENETIC DIVERSITY AND DIGITAL DOCUMENTATION OF KAZAKHSTAN'S FLORA

Kazakhstan, with its expansive and diverse climate zones, boasts a rich and varied flora, featuring around 6,000 vascular species, including approximately 10% that are endemic. Effective management and study of this diverse flora requires continuous monitoring and inventory using advanced botanical, molecular genetic and bioinformatics techniques. This research focuses on exploring the genetic diversity within Kazakhstan's flora and establishing a comprehensive information database. Under Program 0237/PTF (2015-2017), efforts began to assess the genetic diversity of endemic, rare, endangered, and economically significant plant species of Kazakhstan. As part of grant АР05131621, an open-access web resource was developed, offering botanical and genetic data on Kazakhstan's flora. This database includes detailed botanical information on around 500 species. Ongoing research into the genetic diversity of different genera such as Juniperus, Tulipa, Allium, Iris, Salsola, and etc. promises to provide valuable insights into their population structure, phylogenetic relationships, and conservation strategies. Notably, this research has also initiated the first comparative analysis of plastid genomes in Kazakhstan. This research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (AP23490860, AP23483825, AP14870612, АР14869593, AP09259027, 0237/PTF-14, and АР05131621).

ERVcancer: A web resource designed for querying activation of human endogenous retroviruses across major cancer types

Human endogenous retroviruses (HERVs) comprise approximately 8% of the human genome, co-opted into the dynamic regulatory network of cellular potency in early embryonic development. In recent studies, resurgent HERVs' transcriptional activity has been frequently observed in many types of human cancers, suggesting their potential functions in the occurrence and progression of malignancy. However, a dedicated web resource for querying the relationship between activation of HERVs and cancer development is lacking. Here, we have constructed a database to explore the sequence information, expression profiles, survival prognosis, and genetic interactions of HERVs in diverse cancer types. Our database currently contains RNA sequencing data of 580 HERVs across 16,246 samples, including that of 6478 tumoral and 634 normal tissues, 932 cancer cell lines, as well as 151 early embryonic and 8051 human adult tissues. The primary goal is to provide an easily accessible and user-friendly database for professionals in the fields of bioinformatics, pathology, pharmacology, and related areas, enabling them to efficiently screen the activity of HERVs of interest in normal and cancerous tissues and evaluate the clinical relevance. The ERVcancer database is available at http://kyuanlab.com/ervcancer/.

A resource of identified and annotated lincRNAs expressed during somatic embryogenesis development in Norway spruce.

Long non-coding RNAs (lncRNAs) have emerged as important regulators of many biological processes, although their regulatory roles remain poorly characterized in woody plants, especially in gymnosperms. A major challenge of working with lncRNAs is to assign functional annotations, since they have a low coding potential and low cross-species conservation. We utilised an existing RNA-Sequencing resource and performed short RNA sequencing of somatic embryogenesis developmental stages in Norway spruce (Picea abies L. Karst). We implemented a pipeline to identify lncRNAs located within the intergenic space (lincRNAs) and generated a co-expression network including protein coding, lincRNA and miRNA genes. To assign putative functional annotation, we employed a guilt-by-association approach using the co-expression network and integrated these results with annotation assigned using semantic similarity and co-expression. Moreover, we evaluated the relationship between lincRNAs and miRNAs, and identified which lincRNAs are conserved in other species. We identified lincRNAs with clear evidence of differential expression during somatic embryogenesis and used network connectivity to identify those with the greatest regulatory potential. This work provides the most comprehensive view of lincRNAs in Norway spruce and is the first study to perform global identification of lincRNAs during somatic embryogenesis in conifers. The data have been integrated into the expression visualisation tools at the PlantGenIE.org web resource to enable easy access to the community. This will facilitate the use of the data to address novel questions about the role of lincRNAs in the regulation of embryogenesis and facilitate future comparative genomics studies.